Space has long been thought to play a crucial role in the coevolutionary process
Past theoretical work has largely ignored the relationship between coevolution and IBD
Here we outline three projects that attempt to answer the following questions
At what spatial scales do interspecific coevolutionary patterns emerge?
How does this relate to spatial scales of intraspecific local adaptation?
How do these spatial scales and their relationships depend on dispersal distances and environmental heterogeneity?
Can we disentangle the signature of coevolutionary adaptation from isolation by distance?
We focus on host-parasite coevolution
Three projects:
Phenotypic
Two-locus
SLiM
This initial project seeks to answer questions relating to spatial scales of coevolution, local adaptation and environmental heterogeneity using a quantitative-genetic model. By focusing on phenotypic evolution, we may obtain a more broadscale understanding of these phenomena before diving into genetic/genomic details.
This project injects further genetic details by modeling coevolution mediated by two loci in each species. This allows comparisons of intraspecific linkage-disequilibrium to interspecific linkage-disequilibrium, thereby creating the opportunity to distinguish between interspecific linkage due to IBD and coevolution.
This project injects even further genetic details using genome-wide slimulations. Using these individual-based, genome-wide slimulations, we can test conclusions drawn from the simpler, but less realistic approaches taken above to see what we can expect to hold in the wild.
Species \(H\) and \(P\)
Fitness \(m_H,m_P\) determined by quantitative traits \(z_H,z_P\)
Assuming individuals encounter each other at random, mean fitness \(\bar m_H,\bar m_P\) calculated by averaging across \(z_H,z_P\)
Mean trait dynamics given by
\(\frac{d}{dt}\bar z_H=G_H\beta_H+\xi_H\)
\(\frac{d}{dt}\bar z_P=G_P\beta_P+\xi_P\)
\(G_H,G_P\) are additive genetic variances
\(\beta_H,\beta_P\) are selection gradients \(\left(=\frac{\partial\bar m_H}{\partial\bar z_H},\frac{\partial\bar m_P}{\partial\bar z_P}\right)\)
\(\xi_H,\xi_P\) are random processes capturing drift